1 Heatmap Plot of Hourly Rain Data

Below shows a heatmap for hourly rain Campbell data.

Below shows a heatmap for hourly rain HoBo data.

2 Daily rain data

This table shows the data for goodness-of-fit evaluation, location Burn, year 2022.
Time span for the data is 2022-04-02 to 2022-10-11.

3 Goodness-of-fit evaluation between Compbell and Hobo datasets

Goodness-of-fit evaluation starts on 2022-06-15, ends on 2022-09-15. Please see the table below for all indicators.

GOF indicator explanation table (click to unfold)
Indicator name Meaning
me Mean Error
mae Mean Absolute Error
rmse Root Mean Square Error
nrmse Normalized Root Mean Square Error
PBIAS Percent Bias
pbiasfdc PBIAS in the slope of the midsegment of the Flow Duration Curve
RSR Ratio of RMSE to the Standard Deviation of the Observations, RSR = rms / sd(obs). ( 0 <= RSR <= +Inf )
rSD Ratio of Standard Deviations, rSD = sd(sim) / sd(obs)
NSE Nash-Sutcliffe Efficiency ( -Inf <= NSE <= 1 )
mNSE Modified Nash-Sutcliffe Efficiency
rNSE Relative Nash-Sutcliffe Efficiency
d Index of Agreement ( 0 <= d <= 1 )
md Modified Index of Agreement
rd Relative Index of Agreement
cp Persistence Index ( 0 <= PI <= 1 )
r Pearson product-moment correlation coefficient ( -1 <= r <= 1 )
r.Spearman Spearman Correlation coefficient ( -1 <= r.Spearman <= 1 )
R2 Coefficient of Determination ( 0 <= R2 <= 1 ). Gives the proportion of the variance of one variable that is predictable from the other variable
bR2 R2 multiplied by the coefficient of the regression line between sim and obs ( 0 <= bR2 <= 1 )
KGE Kling-Gupta efficiency between sim and obs ( 0 <= KGE <= 1 )
VE Volumetric efficiency between sim and obs( -Inf <= VE <= 1)

4 Rain and Air Temperature

This plot displays the hourly air temperature and rainfall data for both Campbell and Hobo datasets. The corresponding hourly data is also provided in the table below.

This plot displays hourly rainfall data (in mm). Any missing data in the ‘forReview’ Excel table are indicated as -1 in this plot. However, in the data table below, missing values are still denoted as -99.

Please run App.R in RStudio to see the cumulative rainfall plot.